Insights into the Allosteric Response to Acidity by the <i>Helicobacter pylori</i> NikR Transcription Factor
Bibliographic record
Abstract
Helicobacter pylori NikR (HpNikR) is a nickel-responsive transcription factor that regulates genes involved in nickel homeostasis, which is essential for the survival of this pathogen within the acidic human stomach. HpNikR also responds to drops in pH and regulates genes controlling acid acclimation of the bacteria, independently of nickel. We previously showed that nickel binding biases the conformational ensemble of HpNikR to the more DNA-binding competent states via an allosteric network of residues encompassing the nickel binding sites and the interface between the metal- and DNA-binding domains. Here, we examine how acidity promotes this response using 19 F-NMR, mutagenesis, and DNA-binding studies. 19 F-NMR revealed that a drop in pH from 7.6 to 6.0 does little to shift the conformational ensemble of HpNikR to the DNA binding-compatible cis conformer. Nevertheless, DNA-binding affinities of apo-HpNikR at pH 6.0 and Ni(II)-HpNikR at pH 7.6 are comparable for the ureA promoter. Histidine residues of the nickel binding sites were shown to be important for pH-dependent DNA binding and thus likely impart positive charge to the protein, initiating long-range electrostatic interactions with DNA that induce DNA complexation. The results point to a different DNA-binding mechanism in response to acidity compared to the conformational selection mechanism in response to nickel and overall provide new insights into the influence of pH on HpNikR activity, which contributes to H. pylori viability.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".